摘要
脑卒中患者康复治疗中会引起下肢肌肉痉挛,这种现象给患者的康复训练过程带来极大的危害,因此能够在训练过程中识别痉挛并及时中断训练具有重要的实际意义。本研究通对下肢表面肌电信号的采集,采用基于形状的模版匹配法来识别痉挛信号,并以皮尔逊相关系数来分析表征下肢痉挛信号的相关性大小。分析结果表明,通过仿真验证了模版匹配法在个人痉挛信号识别中的准确性,显示了在泛用痉挛信号识别中的可行性。
Rehabilitation treatment of patients with cerebral stroke can cause muscle cramp of lower limbs. This phenomenon will do great harm to the process of rehabilitation training for patients, so it plays an important role in the training process to identify muscle cramp and interrupt training in time. The shape of the template matching method is used to identify spasm signal, and the Pearson correlation coefficient was used to achieve surface electromyography of lower limbs spasm signal template matching analysis. Simulation results demenstrated the accuracy of template matching method in the identification of individual spasm signals, and showed the feasibility of the algorithm in the identification of the nan_
出处
《生物信息学》
2017年第3期186-190,共5页
Chinese Journal of Bioinformatics
基金
上海市科学技术委员会科研计划项目(14441905100)
关键词
表面肌电信号
下肢痉挛信号
模板匹配法
皮尔逊相关系数
Surface electromyography
Muscle cramp of lower limbs signal
Template matching method
Pearson＇scorrelation coefficient
